




'''simple docstring'''


import math

from numpy import inf
from scipy.integrate import quad


def     SCREAMING_SNAKE_CASE							(   a_						:				float      ):
  if num <= 0:
    raise ValueError('math domain error'      )

  return quad(a_					,       0					,       a_					,       args=(a_)      )[0]


def     SCREAMING_SNAKE_CASE							(   a_						:				float					,       a_						:				float      ):
  return math.pow(a_					,       z - 1      ) * math.exp(-x      )


if __name__ == "__main__":
  from doctest import testmod

  testmod()









'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


UpperCAmelCase_					=   {"configuration_swin": ["SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwinConfig", "SwinOnnxConfig"]}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_					=   [
      "SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
      "SwinForImageClassification",
      "SwinForMaskedImageModeling",
      "SwinModel",
      "SwinPreTrainedModel",
      "SwinBackbone",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_					=   [
      "TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
      "TFSwinForImageClassification",
      "TFSwinForMaskedImageModeling",
      "TFSwinModel",
      "TFSwinPreTrainedModel",
  ]

if TYPE_CHECKING:
  from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_swin import (
        SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
        SwinBackbone,
        SwinForImageClassification,
        SwinForMaskedImageModeling,
        SwinModel,
        SwinPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_swin import (
        TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFSwinForImageClassification,
        TFSwinForMaskedImageModeling,
        TFSwinModel,
        TFSwinPreTrainedModel,
    )

else:
  import sys

  UpperCAmelCase_					=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



